Many industrial facilities and processes are heavily dependent on rotating machines or other machines with cyclic motion, for instance pumps, compressors, fans, motors, engines, etc. Such machines encounter failures in normal operations due to internal wear of parts, breakdown of mounts, loosening of fasteners, etc. A terminal or catastrophic failure of such a machine can be very costly because it may halt a process until the machine can be repaired, or a failure of one part may lead to failures in other parts of the system, incurring more costs. In some applications machine failures may also pose a significant safety hazard. Thus, early detection of impending failure is highly desirable, such that the machine can be maintained or repaired in a pro-active manner before a catastrophic failure occurs, rather than repairing reactively after a costly failure has already occurred. Many problems such as bearing degradation, gear failures, imbalances, etc. which may eventually lead to an expensive failure can be diagnosed prior to failure by monitoring the vibration of the machine at one or more points. Therefore it is desirable to instrument high-value or safety-critical machines with vibration sensors which can be monitored periodically to judge the health of the machine and help inform maintenance activities.
Maintenance and inspection requirements often drive the life-cycle cost of components and structures, particularly for fatigue sensitive and operation critical parts. Maintenance activities are often conducted on time intervals that are based on worst case environmental, wear, and loading conditions. However in practice component and structure usage conditions vary and therefore, structural degradation varies between each asset, making failure difficult to predict purely on usage time. Acquisition of health and usage data during use of the component or structure promises to enable tailoring of maintenance activities to each asset and thereby reduce over-conservative maintenance activity. This practice of Condition Based Maintenance (CBM) and Structural Health Monitoring (SHM) is particularly relevant to high-value assets that require expensive and frequent maintenance. In the context of such machines, the application of CBM practices reduces scheduled and unscheduled maintenance, reduces inspection requirements, and extends the life of certain components and subsystems. In the case of structures and dynamic systems, physical sensors are required to generate factual data upon which maintenance decisions are based. In many conventional CBM implementations, sensors are wired to a data aggregator and processing unit. Alternatively a “walk-around” system may be used, in which an operator must take a limited number of sensors from machine to machine to collect periodic measurements. As sensor technology and CBM analysis techniques have improved, sensor wiring and walk-around operation have become major limitations to establishing favorable CBM life-cycle value statements for many applications.
Wireless technologies promises to address this problem by simplifying and reducing the cost of installation, reducing maintenance associated with wiring faults, reducing the need for a technician to visit each monitoring location, and increasing the quantity of data that can be collected. To realize these benefits in most cases, wireless communication must be similar in robustness and function to wired systems, sensor weight including autonomous power supplies must be less than that of a wired sensor, and sensor capability must be similar to their wired counterparts. Satisfying these requirements is a challenge because sensor power supply capability (life or average power delivery) scales directly with weight, and wireless sensor performance, including RF transmission robustness and sensor capability, depends on the energy offered by the power supply.
The fundamental approach to optimally satisfying these requirements seeks to maximize the measurement accuracy of extremely low-power sensor elements such that a wireless accelerometer can be used for a very long period of time with high accuracy in a very small package with a small power source (battery). Novel solutions to these issues are presented in the following disclosure.